Case Study: maps and models to support winegrowers

Introduction

Viticulture has ancient roots that coincide with the emergence of the first civilisations and has had a significant impact on the development of our society. Over the millennia, we have witnessed significant transformations, both in terms of the grape varieties grown and the farming methods used to cultivate them. Today, mainly due to rapid climate change and significant environmental impact, we face a set of considerable challenges. Protecting vineyards and preventing harmful events such as hailstorms, frost and disease, while respecting the environment, is becoming increasingly difficult. To better tackle these issues, a range of innovative tools are available to help businesses manage their vineyards and increase the quality of the finished product.

Fig.1: Trellised vineyard

iDrone: variability maps generated by drone

By analysing visible (RGB), multispectral and/or thermal images taken by drone (see the iDrone service), it is possible to reconstruct thematic vineyard maps, such as NDVI (Normalized Difference Vegetation Index) maps, an important tool used to monitor and assess vineyard vigour (Fig. 2).

The maps can be used for various purposes:

1. Streamlined crop protection treatments

Vigour maps make it possible to identify and characterise field variability, allowing zoning maps to be created that, once loaded onto variable rate (VRT) machinery, make it possible to concentrate treatments in more vigorous areas and apply less product in less vigorous areas, optimising the use of water and pesticides.

2. Selective harvesting

NDVI-based maps can help identify the different vigour zones in the field where grapes have reached different degrees of ripeness. This is particularly useful when growing different grape varieties or when aiming to produce high-quality wines. Vigour maps allow farmers to plan the harvest more efficiently, harvesting grapes in the ripest zones at specific times, improving the quality of the finished product. To find out more, you can watch the webinar we held on this topic -> Vineyard zoning for a precision harvest

3. Differentiated fertilisation

With vigour maps, it is possible to adapt fertilisation to the specific needs of vines in each area of the vineyard. This allows for more precise nutrient management, avoiding waste and improving distribution based on where nutrient needs are greatest. If carried out correctly, differentiated fertilisation based on vigour maps helps to optimise fertiliser use. Indeed, by distributing a smaller amount of fertiliser in already-vigorous areas while applying a larger amount in less vigorous areas, field redistribution is improved and variability is reduced.

4. Managing water stress

Using thermal cameras mounted on drones, temperature maps can be generated to consciously manage water stress. These maps provide information on the temperature of vines and soil, helping to identify areas subject to water stress. These critical areas can be identified in a timely manner in order to take preventive action and define targeted irrigation scheduling, allowing winegrowers to make more informed irrigation decisions for more conscious use of water resources. The CWSI (Crop Water Stress Index) is an indicator used in agriculture to assess the level of water stress in crops. The maps can indicate the areas of the vineyard that need irrigation or that have drainage problems or waterlogging, allowing for targeted management of water resources to improve plant wellbeing, reducing the risk of incorrect irrigation management.

Fig.2: Vigour map of a vineyard in three classes: low, medium, high

iAgro: precision viticulture from a smartphone

Among Agrobit’s solutions is also iAgro, the first site-specific mobile DSS app capable of optimising crop protection treatments and creating vineyard vigour maps simply using your smartphone.

With iAgro, through a photographic scan of a vine or a section of a row (Fig. 3), it is possible to quickly and objectively measure several parameters, in particular:

• the height, thickness and canopy volume of the scanned plant;
• the Leaf Area Index (LAI);
• the Leaf Wall Area (LWA);
• the Tree Row Volume (TRV);
• the optimal water dose for crop protection treatments at each phenological stage.

Fig.3: 3D point cloud of a vine generated by the iAgro app

By sampling a sufficient number of well-distributed plants in the field (at least 5 points per field), the app automatically generates vegetative vigour maps (LAI index), which can be used to optimise fertilisation or grape harvesting, and prescription maps for variable, optimised crop protection treatments, based on the vineyard’s actual needs at each phenological stage recorded (Fig. 4).

Fig.4: Vigour map (LAI index) in 3 classes generated by the iAgro app (in yellow, the points scanned with the app), which can be used to optimise fertilisation and grape harvesting. Whiter zones correspond to lower vigour compared with greener zones, which have higher vegetative vigour.

Depending on the type of treatment and the farm’s sprayer, the app will be able to create a prescription map for the correct dose of water and pesticide to be applied (Fig. 5), always in accordance with the manufacturer’s label. Thanks to iAgro, it is possible to save up to 60% of water per treatment and distribute pesticides more effectively, with positive economic, environmental and social implications.

Fig.5: Water dose prescription map (l/ha) in 3 classes generated by the iAgro app (in yellow, the points scanned with the app), which can be used to optimise crop protection treatments, including by loading it directly onto variable rate (VRT) machinery

Weather stations, DSS and forecasting models

In the context of quality viticulture, weather stations and forecasting models are irreplaceable tools that form genuine agronomic decision support systems (DSS, Decision Support System). Their importance is crucial, as they provide essential data for optimal vineyard management and for making informed decisions based on information from the field (soil and microclimate).

Weather stations collect real-time weather data, such as temperature, humidity, rainfall, leaf wetness, wind speed and direction, etc., while forecasting models use this data, together with accurate weather forecasts and mechanistic models based on vine biology, to provide useful decision support information such as:

• crop phenology (development stage or ripening stage);
• the risk of pathogen infestation at each point in the growing cycle;
• nutritional and water requirements.

An example of a DSS for viticulture is GrapeDSS, an Agricolus solution that provides a range of very useful information for farmers, including:

• Phenological model: phenology forecasting to assess the olive grove’s needs at each stage of development;
• Irrigation requirement estimate: to intervene when necessary with the optimal water supply;
• Fertilisation model: calculation of total nitrogen, phosphorus and potassium requirements to provide suggestions on fertiliser doses to apply;
• Forecasting models for diseases (downy mildew, powdery mildew, botrytis) and harmful insects (European grapevine moth): the risks from pathogens such as downy mildew, powdery mildew and botrytis are forecast by analysing microclimatic data (Fig. 6), as are infestations of the European grapevine moth, for which the model is able to simulate the development of the generations that occur during the season, allowing winegrowers to adopt preventive measures and treat more efficiently and effectively.

Fig.6: Forecasting model for Plasmopara viticola (top) and Lobesia botrana (bottom)

Conclusions

Managing the vineyard with pesticides and fertilisers has a significant impact on a business’s economic and environmental balance. It is important to implement the streamlining of farming practices that characterise vineyard management, using tools that reduce environmental impact, making the business more sustainable and competitive on the market and in line with new regulations (European Green Deal and Farm-to-Fork Strategy).

Using vineyard vigour maps, generated with the iDrone service or independently with the iAgro app, allows farmers to adopt a more targeted, sustainable approach to vine management, improving the quality of the finished product and reducing resource waste. This operational strategy stands out for its notable robustness in outlining the vineyard’s specific characteristics, focusing in particular on defining the variability naturally present in the field, allowing the business to build an increasingly precise identity and stand out on the market.

Using weather stations and forecasting models allows winegrowers to make decisions based on scientific data and reduce risks, improving grape quality and yield and, as a result, wine production. In the wine sector, where temperature variations affect all the physiological processes governing phenological and physiological development, the ability to constantly forecast and monitor this type of information is essential for ensuring a high level of control over grape quality and adequate productivity. By using weather stations and forecasting models, winegrowers can act at the optimal times, optimising crop protection operations and resource use, reducing waste and improving production efficiency.